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Quek YE, Fung YL, Cheung MWL, Vogrin SJ, Collins SJ, Bowden SC. Agreement Between Automated and Manual MRI Volumetry in Alzheimer's Disease: A Systematic Review and Meta-Analysis. J Magn Reson Imaging 2021; 56:490-507. [PMID: 34964531 DOI: 10.1002/jmri.28037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Automated magnetic resonance imaging (MRI) volumetry is a promising tool to evaluate regional brain volumes in dementia and especially Alzheimer's disease (AD). PURPOSE To compare automated methods and the gold standard manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD. STUDY TYPE Systematic review and meta-analysis. DATA SOURCES MEDLINE, Embase, and PsycINFO were searched through October 2021. FIELD STRENGTH 1.0 T, 1.5 T, or 3.0 T. ASSESSMENT Two review authors independently identified studies for inclusion and extracted data. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). STATISTICAL TESTS Standardized mean differences (SMD; Hedges' g) were pooled using random-effects meta-analysis with robust variance estimation. Subgroup analyses were undertaken to explore potential sources of heterogeneity. Sensitivity analyses were conducted to examine the impact of the within-study correlation between effect estimates on the meta-analysis results. RESULTS Seventeen studies provided sufficient data to evaluate the hippocampus, lateral ventricles, and parahippocampal gyrus. The pooled SMD for the hippocampus, lateral ventricles, and parahippocampal gyrus were 0.22 (95% CI -0.50 to 0.93), 0.12 (95% CI -0.13 to 0.37), and -0.48 (95% CI -1.37 to 0.41), respectively. For the hippocampal data, subgroup analyses suggested that the pooled SMD was invariant across clinical diagnosis and field strength. Subgroup analyses could not be conducted on the lateral ventricles data and the parahippocampal gyrus data due to insufficient data. The results were robust to the selected within-study correlation value. DATA CONCLUSION While automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, wide 95% CIs and large heterogeneity suggest that there is substantial uncontrolled variance. Thus, automated methods may be used to measure these regions in patients with AD but should be used with caution. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Yi-En Quek
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Yi Leng Fung
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Mike W-L Cheung
- Department of Psychology, Faculty of Arts and Social Sciences, National University of Singapore, Singapore
| | - Simon J Vogrin
- Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
| | - Steven J Collins
- Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
| | - Stephen C Bowden
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.,Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
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Zhang J, Liu Y, Lan K, Huang X, He Y, Yang F, Li J, Hu Q, Xu J, Yu H. Gray Matter Atrophy in Amnestic Mild Cognitive Impairment: A Voxel-Based Meta-Analysis. Front Aging Neurosci 2021; 13:627919. [PMID: 33867968 PMCID: PMC8044397 DOI: 10.3389/fnagi.2021.627919] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 03/02/2021] [Indexed: 12/13/2022] Open
Abstract
Background: Voxel-based morphometry (VBM) has been widely used to investigate structural alterations in amnesia mild cognitive impairment (aMCI). However, inconsistent results have hindered our understanding of the exact neuropathology related to aMCI. Objectives: Our aim was to systematically review the literature reporting VBM on aMCI to elucidate consistent gray matter alterations, their functional characterization, and corresponding co-activation patterns. Methods: The PubMed, Web of Science, and EMBASE databases were searched for VBM studies on aMCI published from inception up to June 2020. Peak coordinates were extracted from clusters that showed significant gray matter differences between aMCI patients and healthy controls (HC). Meta-analysis was performed using seed-based d mapping with the permutation of subject images (SDM-PSI), a newly improved meta-analytic method. Functional characterization and task-based co-activation patterns using the BrainMap database were performed on significant clusters to explore their functional roles. Finally, VBM was performed based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to further support the findings. Results: A total of 31 studies with 681 aMCI patients and 837 HC were included in this systematic review. The aMCI group showed significant gray matter atrophy in the left amygdala and right hippocampus, which was consistent with results from the ADNI dataset. Functional characterization revealed that these regions were mainly associated with emotion, cognition, and perception. Further, meta-regression analysis demonstrated that gray matter atrophy in the left inferior frontal gyrus and the left angular gyrus was significantly associated with cognitive impairment in the aMCI group. Conclusions: The findings of gray matter atrophy in the left amygdala and right hippocampus are highly consistent and robust, and not only offer a better understanding of the underlying neuropathology but also provide accurate potential biomarkers for aMCI.
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Affiliation(s)
- Jinhuan Zhang
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.,Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yongfeng Liu
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Kai Lan
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Xingxian Huang
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Yuhai He
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Fuxia Yang
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Jiaying Li
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Qingmao Hu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Haibo Yu
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.,Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
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Lombardi G, Crescioli G, Cavedo E, Lucenteforte E, Casazza G, Bellatorre A, Lista C, Costantino G, Frisoni G, Virgili G, Filippini G. Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment. Cochrane Database Syst Rev 2020; 3:CD009628. [PMID: 32119112 PMCID: PMC7059964 DOI: 10.1002/14651858.cd009628.pub2] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year. OBJECTIVES To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI. SEARCH METHODS On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches. SELECTION CRITERIA We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter. DATA COLLECTION AND ANALYSIS Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available. MAIN RESULTS We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate. AUTHORS' CONCLUSIONS The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.
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Affiliation(s)
- Gemma Lombardi
- University of FlorenceDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA)Largo Brambilla, 3FlorenceItaly50134
| | - Giada Crescioli
- University of FlorenceDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA)Largo Brambilla, 3FlorenceItaly50134
| | - Enrica Cavedo
- Pitie‐Salpetriere Hospital, Sorbonne UniversityAlzheimer Precision Medicine (APM), AP‐HP47 boulevard de l'HopitalParisFrance75013
| | - Ersilia Lucenteforte
- University of PisaDepartment of Clinical and Experimental MedicineVia Savi 10PisaItaly56126
| | - Giovanni Casazza
- Università degli Studi di MilanoDipartimento di Scienze Biomediche e Cliniche "L. Sacco"via GB Grassi 74MilanItaly20157
| | | | - Chiara Lista
- Fondazione I.R.C.C.S. Istituto Neurologico Carlo BestaNeuroepidemiology UnitVia Celoria, 11MilanoItaly20133
| | - Giorgio Costantino
- Ospedale Maggiore Policlinico, Università degli Studi di MilanoUOC Pronto Soccorso e Medicina D'Urgenza, Fondazione IRCCS Ca' GrandaMilanItaly
| | | | - Gianni Virgili
- University of FlorenceDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA)Largo Brambilla, 3FlorenceItaly50134
| | - Graziella Filippini
- Carlo Besta Foundation and Neurological InstituteScientific Director’s Officevia Celoria, 11MilanItaly20133
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Bartel F, Visser M, de Ruiter M, Belderbos J, Barkhof F, Vrenken H, de Munck JC, van Herk M. Non-linear registration improves statistical power to detect hippocampal atrophy in aging and dementia. Neuroimage Clin 2019; 23:101902. [PMID: 31233953 PMCID: PMC6595082 DOI: 10.1016/j.nicl.2019.101902] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 05/01/2019] [Accepted: 06/16/2019] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To compare the performance of different methods for determining hippocampal atrophy rates using longitudinal MRI scans in aging and Alzheimer's disease (AD). BACKGROUND Quantifying hippocampal atrophy caused by neurodegenerative diseases is important to follow the course of the disease. In dementia, the efficacy of new therapies can be partially assessed by measuring their effect on hippocampal atrophy. In radiotherapy, the quantification of radiation-induced hippocampal volume loss is of interest to quantify radiation damage. We evaluated plausibility, reproducibility and sensitivity of eight commonly used methods to determine hippocampal atrophy rates using test-retest scans. MATERIALS AND METHODS Manual, FSL-FIRST, FreeSurfer, multi-atlas segmentation (MALF) and non-linear registration methods (Elastix, NiftyReg, ANTs and MIRTK) were used to determine hippocampal atrophy rates on longitudinal T1-weighted MRI from the ADNI database. Appropriate parameters for the non-linear registration methods were determined using a small training dataset (N = 16) in which two-year hippocampal atrophy was measured using test-retest scans of 8 subjects with low and 8 subjects with high atrophy rates. On a larger dataset of 20 controls, 40 mild cognitive impairment (MCI) and 20 AD patients, one-year hippocampal atrophy rates were measured. A repeated measures ANOVA analysis was performed to determine differences between controls, MCI and AD patients. For each method we calculated effect sizes and the required sample sizes to detect one-year volume change between controls and MCI (NCTRL_MCI) and between controls and AD (NCTRL_AD). Finally, reproducibility of hippocampal atrophy rates was assessed using within-session rescans and expressed as an average distance measure DAve, which expresses the difference in atrophy rate, averaged over all subjects. The same DAve was used to determine the agreement between different methods. RESULTS Except for MALF, all methods detected a significant group difference between CTRL and AD, but none could find a significant difference between the CTRL and MCI. FreeSurfer and MIRTK required the lowest sample sizes (FreeSurfer: NCTRL_MCI = 115, NCTRL_AD = 17 with DAve = 3.26%; MIRTK: NCTRL_MCI = 97, NCTRL_AD = 11 with DAve = 3.76%), while ANTs was most reproducible (NCTRL_MCI = 162, NCTRL_AD = 37 with DAve = 1.06%), followed by Elastix (NCTRL_MCI = 226, NCTRL_AD = 15 with DAve = 1.78%) and NiftyReg (NCTRL_MCI = 193, NCTRL_AD = 14 with DAve = 2.11%). Manually measured hippocampal atrophy rates required largest sample sizes to detect volume change and were poorly reproduced (NCTRL_MCI = 452, NCTRL_AD = 87 with DAve = 12.39%). Atrophy rates of non-linear registration methods also agreed best with each other. DISCUSSION AND CONCLUSION Non-linear registration methods were most consistent in determining hippocampal atrophy and because of their better reproducibility, methods, such as ANTs, Elastix and NiftyReg, are preferred for determining hippocampal atrophy rates on longitudinal MRI. Since performances of non-linear registration methods are well comparable, the preferred method would mostly depend on computational efficiency.
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Affiliation(s)
- F Bartel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
| | - M Visser
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - M de Ruiter
- Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - J Belderbos
- Department of Radiotherapy, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - F Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands; UCL institutes of Neurology and healthcare engineering, London, United Kingdom
| | - H Vrenken
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - J C de Munck
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - M van Herk
- Manchester Cancer Research Centre, Division of Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom
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5
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Elhaik Goldman S, Goez D, Last D, Naor S, Liraz Zaltsman S, Sharvit-Ginon I, Atrakchi-Baranes D, Shemesh C, Twitto-Greenberg R, Tsach S, Lotan R, Leikin-Frenkel A, Shish A, Mardor Y, Schnaider Beeri M, Cooper I. High-fat diet protects the blood-brain barrier in an Alzheimer's disease mouse model. Aging Cell 2018; 17:e12818. [PMID: 30079520 PMCID: PMC6156545 DOI: 10.1111/acel.12818] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Revised: 06/12/2018] [Accepted: 06/24/2018] [Indexed: 12/13/2022] Open
Abstract
Type 2 diabetes (T2D) is associated with increased risk of Alzheimer's disease (AD). There is evidence for impaired blood-brain barrier (BBB) in both diseases, but its role in the interplay between them is not clear. Here, we investigated the effects of high-fat diet (HFD), a model for T2D, on the Tg2576 mouse model of AD, in regard to BBB function. We showed that HFD mice had higher weight, more insulin resistance, and higher serum HDL cholesterol levels, primarily in Tg2576 mice, which also had higher brain lipids content. In terms of behavior, Tg2576 HFD mice were less active and more anxious, but had better learning in the Morris Water Maze compared to Tg2576 on regular diet. HFD had no effect on the level of amyloid beta 1-42 in the cortex of Tg2576 mice, but increased the transcription level of insulin receptor in the hippocampus. Tg2576 mice on regular diet demonstrated more BBB disruption at 8 and 12 months accompanied by larger lateral ventricles volume in contrast to Tg2576 HFD mice, whose BBB leakage and ventricular volume were similar to wild-type (WT) mice. Our results suggest that in AD, HFD may promote better cognitive function through improvements of BBB function and of brain atrophy but not of amyloid beta levels. Lipid metabolism in the CNS and peripheral tissues and brain insulin signaling may underlie this protection.
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Affiliation(s)
- Shirin Elhaik Goldman
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
- Gonda Brain Research Center; Bar Ilan University; Ramat-Gan Israel
| | - David Goez
- The Advanced Technology Center, Sheba Medical Center; Tel-Hashomer; Ramat-Gan Israel
| | - David Last
- The Advanced Technology Center, Sheba Medical Center; Tel-Hashomer; Ramat-Gan Israel
| | - Sharone Naor
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
| | - Sigal Liraz Zaltsman
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
- Pharmacology Division, Faculty of Medicine, The Institute for Drug Research, School of Pharmacy; Hebrew University of Jerusalem; Jerusalem Israel
| | - Inbal Sharvit-Ginon
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
- Department of Psychology; Bar Ilan University; Ramat-Gan Israel
| | - Dana Atrakchi-Baranes
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
| | - Chen Shemesh
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
| | - Rachel Twitto-Greenberg
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
- The Bert W. Strassburger Lipid Center, Sheba Medical Center; Tel-Hashomer; Ramat-Gan Israel
| | - Shoval Tsach
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
| | - Roni Lotan
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
| | - Alicia Leikin-Frenkel
- The Bert W. Strassburger Lipid Center, Sheba Medical Center; Tel-Hashomer; Ramat-Gan Israel
- Sackler Faculty of Medicine; Tel-Aviv University; Tel-Aviv Israel
| | - Aviv Shish
- The Bert W. Strassburger Lipid Center, Sheba Medical Center; Tel-Hashomer; Ramat-Gan Israel
| | - Yael Mardor
- The Advanced Technology Center, Sheba Medical Center; Tel-Hashomer; Ramat-Gan Israel
- Sackler Faculty of Medicine; Tel-Aviv University; Tel-Aviv Israel
| | - Michal Schnaider Beeri
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
- Department of Psychiatry; The Icahn School of Medicine at Mount Sinai; New York New York
- The Interdisciplinary Center; Herzliya Israel
| | - Itzik Cooper
- The Joseph Sagol Neuroscience Center, Sheba Medical Center; Tel Hashomer; Ramat Gan Israel
- The Interdisciplinary Center; Herzliya Israel
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Cover KS, van Schijndel RA, Versteeg A, Leung KK, Mulder ER, Jong RA, Visser PJ, Redolfi A, Revillard J, Grenier B, Manset D, Damangir S, Bosco P, Vrenken H, van Dijk BW, Frisoni GB, Barkhof F. Reproducibility of hippocampal atrophy rates measured with manual, FreeSurfer, AdaBoost, FSL/FIRST and the MAPS-HBSI methods in Alzheimer's disease. Psychiatry Res Neuroimaging 2016; 252:26-35. [PMID: 27179313 DOI: 10.1016/j.pscychresns.2016.04.006] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Revised: 02/16/2016] [Accepted: 04/08/2016] [Indexed: 11/23/2022]
Abstract
The purpose of this study is to assess the reproducibility of hippocampal atrophy rate measurements of commonly used fully-automated algorithms in Alzheimer disease (AD). The reproducibility of hippocampal atrophy rate for FSL/FIRST, AdaBoost, FreeSurfer, MAPS independently and MAPS combined with the boundary shift integral (MAPS-HBSI) were calculated. Back-to-back (BTB) 3D T1-weighted MPRAGE MRI from the Alzheimer's Disease Neuroimaging Initiative (ADNI1) study at baseline and year one were used. Analysis on 3 groups of subjects was performed - 562 subjects at 1.5T, a 75 subject group that also had manual segmentation and 111 subjects at 3T. A simple and novel statistical test based on the binomial distribution was used that handled outlying data points robustly. Median hippocampal atrophy rates were -1.1%/year for healthy controls, -3.0%/year for mildly cognitively impaired and -5.1%/year for AD subjects. The best reproducibility was observed for MAPS-HBSI (1.3%), while the other methods tested had reproducibilities at least 50% higher at 1.5T and 3T which was statistically significant. For a clinical trial, MAPS-HBSI should require less than half the subjects of the other methods tested. All methods had good accuracy versus manual segmentation. The MAPS-HBSI method has substantially better reproducibility than the other methods considered.
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Affiliation(s)
- Keith S Cover
- VU University Medical Center, Amsterdam, Netherlands.
| | | | | | | | - Emma R Mulder
- VU University Medical Center, Amsterdam, Netherlands
| | - Remko A Jong
- VU University Medical Center, Amsterdam, Netherlands
| | | | | | | | | | | | | | - Paolo Bosco
- IRCCS San Giovanni di Dio Fatebenefratelli, Italy
| | - Hugo Vrenken
- VU University Medical Center, Amsterdam, Netherlands
| | | | - Giovanni B Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Italy; University Hospitals and University of Geneva, Switzerland
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Tang X, Holland D, Dale AM, Younes L, Miller MI. The diffeomorphometry of regional shape change rates and its relevance to cognitive deterioration in mild cognitive impairment and Alzheimer's disease. Hum Brain Mapp 2015; 36:2093-117. [PMID: 25644981 DOI: 10.1002/hbm.22758] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2014] [Revised: 12/07/2014] [Accepted: 01/26/2015] [Indexed: 01/21/2023] Open
Abstract
We proposed a diffeomorphometry-based statistical pipeline to study the regional shape change rates of the bilateral hippocampus, amygdala, and ventricle in mild cognitive impairment (MCI) and Alzheimer's disease (AD) compared with healthy controls (HC), using sequential magnetic resonance imaging (MRI) scans of 713 subjects (3,123 scans in total). The subgroup shape atrophy rates of the bilateral hippocampus and amygdala, as well as the expansion rates of the bilateral ventricles, for a majority of vertices were found to follow the order of AD>MCI>HC. The bilateral hippocampus and the left amygdala were subsegmented into multiple functionally meaningful subregions with the help of high-field MRI scans. The largest group differences in localized shape atrophy rates on the hippocampus were found to occur in CA1, followed by subiculum, CA2, and finally CA3/dentate gyrus, which is consistent with the neurofibrillary tangle accumulation trajectory. Highly nonuniform group differences were detected on the amygdala; vertices on the core amygdala (basolateral and lateral nucleus) revealed much larger atrophy rates, whereas those on the noncore amygdala (mainly centromedial) displayed similar or even smaller atrophy rates in AD relative to HC. The temporal horns of the ventricles were observed to have the largest localized ventricular expansion rate differences; with the AD group showing larger localized expansion rates on the anterior horn and the body part of the ventricles as well. Significant correlations were observed between the localized shape change rates of each of these six structures and the cognitive deterioration rates as quantified by the Alzheimer's Disease Assessment Scale-Cognitive Behavior Section increase rate and the Mini Mental State Examination decrease rate.
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Affiliation(s)
- Xiaoying Tang
- Whiting School of Engineering, Center for Imaging Science, Johns Hopkins University, Baltimore, Maryland
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8
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Chang HH, Tsai CY. Adaptive registration of magnetic resonance images based on a viscous fluid model. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2014; 117:80-91. [PMID: 25176596 DOI: 10.1016/j.cmpb.2014.08.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2014] [Revised: 08/08/2014] [Accepted: 08/12/2014] [Indexed: 06/03/2023]
Abstract
This paper develops a new viscous fluid registration algorithm that makes use of a closed incompressible viscous fluid model associated with mutual information. In our approach, we treat the image pixels as the fluid elements of a viscous fluid governed by the nonlinear Navier-Stokes partial differential equation (PDE) that varies in both temporal and spatial domains. We replace the pressure term with an image-based body force to guide the transformation that is weighted by the mutual information between the template and reference images. A computationally efficient algorithm with staggered grids is introduced to obtain stable solutions of this modified PDE for transformation. The registration process of updating the body force, the velocity and deformation fields is repeated until the mutual information reaches a prescribed threshold. We have evaluated this new algorithm in a number of synthetic and medical images. As consistent with the theory of the viscous fluid model, we found that our method faithfully transformed the template images into the reference images based on the intensity flow. Experimental results indicated that the proposed scheme achieved stable registrations and accurate transformations, which is of potential in large-scale medical image deformation applications.
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Affiliation(s)
- Herng-Hua Chang
- Computational Biomedical Engineering Laboratory (CBEL), Department of Engineering Science and Ocean Engineering, National Taiwan University, Daan, 10617 Taipei, Taiwan.
| | - Chih-Yuan Tsai
- Computational Biomedical Engineering Laboratory (CBEL), Department of Engineering Science and Ocean Engineering, National Taiwan University, Daan, 10617 Taipei, Taiwan
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Prins ND, van der Flier WA, Knol DL, Fox NC, Brashear HR, Nye JS, Barkhof F, Scheltens P. The effect of galantamine on brain atrophy rate in subjects with mild cognitive impairment is modified by apolipoprotein E genotype: post-hoc analysis of data from a randomized controlled trial. ALZHEIMERS RESEARCH & THERAPY 2014; 6:47. [PMID: 25478019 PMCID: PMC4255389 DOI: 10.1186/alzrt275] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/18/2013] [Accepted: 06/27/2014] [Indexed: 12/13/2022]
Abstract
INTRODUCTION The aim of this investigation was to assess the effect of galantamine, an acetylcholinesterase inhibitor and allosteric modulator of nicotinic receptors, on brain atrophy in individuals with mild cognitive impairment (MCI), and to assess effect modification by apolipoprotein E (APOE) genotype. METHODS We used data from the Galantamine-International-11 (Gal-Int-11) trial, a 24-month, randomized, double blind, placebo-controlled, flexible-dose (16 to 24 mg daily) study in patients with MCI. Brain magnetic resonance imaging (MRI), including a 3-dimensional T1-weighted gradient echo volumetric sequence, was performed at screening and at 24 months. We recorded whole brain and hippocampal volumes, and calculated annual atrophy rates. Linear regression analysis was used to calculate adjusted mean differences in the rate of whole brain and hippocampal atrophy, between MCI patients treated with galantamine and with placebo. Additionally, we performed stratified analyses according to APOE genotype. RESULTS Data from 364 MCI patients with 24-month MRI data (galantamine, n = 176; placebo, n = 188) were included in the volumetric analysis. Subjects treated with galantamine demonstrated a lower rate of whole brain atrophy compared to those treated with placebo (adjusted mean difference 0.18% per year (95% confidence interval (CI) 0.04; 0.30)). Stratified analyses according to APOE genotype, showed that this effect was confined to patients who carried an APOE ϵ4 allele (adjusted mean difference 0.28% per year (95% CI 0.07; 0.50)). Rates of hippocampal atrophy did not differ significantly between study groups. CONCLUSIONS Patients with MCI who were treated with galantamine demonstrated a lower rate of whole brain atrophy, but not of hippocampal atrophy, over a 24-month treatment period, compared to those treated with placebo. This protective effect of galantamine on whole brain atrophy rate in MCI was only present in APOE ϵ4 carriers.
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Affiliation(s)
- Niels D Prins
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, PO Box 7057, 1007 MB Amsterdam, the Netherlands ; Alzheimer Research Center, Gebouw Cronenburg, Cronenburg 75, 1081 GM Amsterdam, the Netherlands
| | - Wiesje A van der Flier
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, PO Box 7057, 1007 MB Amsterdam, the Netherlands ; Alzheimer Research Center, Gebouw Cronenburg, Cronenburg 75, 1081 GM Amsterdam, the Netherlands
| | - Dirk L Knol
- Department of Epidemiology & Biostatistics, VU University Medical Centre, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Nick C Fox
- Dementia Research Centre (N.C.F.), Department of Neurodegenerative Disease, Institute of Neurology, University College London, 8-11 Queen Square, London WC1N 3BG, UK
| | - H Robert Brashear
- Janssen Alzheimer Immunotherapy Research and Development, 700 Gateway Blvd, South San Francisco, CA 94080, USA
| | - Jeffrey S Nye
- Janssen Research and Development, LLC Johnson and Johnson Innovation, One Cambridge Center, 7th Floor, Cambridge, MA 02142, USA
| | - Frederik Barkhof
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, PO Box 7057, 1007 MB Amsterdam, the Netherlands ; Department of Radiology, Image Analysis Centre, VU University Medical Centre, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, PO Box 7057, 1007 MB Amsterdam, the Netherlands
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10
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Mulder ER, de Jong RA, Knol DL, van Schijndel RA, Cover KS, Visser PJ, Barkhof F, Vrenken H. Hippocampal volume change measurement: quantitative assessment of the reproducibility of expert manual outlining and the automated methods FreeSurfer and FIRST. Neuroimage 2014; 92:169-81. [PMID: 24521851 DOI: 10.1016/j.neuroimage.2014.01.058] [Citation(s) in RCA: 101] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2013] [Revised: 01/23/2014] [Accepted: 01/31/2014] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND To measure hippocampal volume change in Alzheimer's disease (AD) or mild cognitive impairment (MCI), expert manual delineation is often used because of its supposed accuracy. It has been suggested that expert outlining yields poorer reproducibility as compared to automated methods, but this has not been investigated. AIM To determine the reproducibilities of expert manual outlining and two common automated methods for measuring hippocampal atrophy rates in healthy aging, MCI and AD. METHODS From the Alzheimer's Disease Neuroimaging Initiative (ADNI), 80 subjects were selected: 20 patients with AD, 40 patients with mild cognitive impairment (MCI) and 20 healthy controls (HCs). Left and right hippocampal volume change between baseline and month-12 visit was assessed by using expert manual delineation, and by the automated software packages FreeSurfer (longitudinal processing stream) and FIRST. To assess reproducibility of the measured hippocampal volume change, both back-to-back (BTB) MPRAGE scans available for each visit were analyzed. Hippocampal volume change was expressed in μL, and as a percentage of baseline volume. Reproducibility of the 1-year hippocampal volume change was estimated from the BTB measurements by using linear mixed model to calculate the limits of agreement (LoA) of each method, reflecting its measurement uncertainty. Using the delta method, approximate p-values were calculated for the pairwise comparisons between methods. Statistical analyses were performed both with inclusion and exclusion of visibly incorrect segmentations. RESULTS Visibly incorrect automated segmentation in either one or both scans of a longitudinal scan pair occurred in 7.5% of the hippocampi for FreeSurfer and in 6.9% of the hippocampi for FIRST. After excluding these failed cases, reproducibility analysis for 1-year percentage volume change yielded LoA of ±7.2% for FreeSurfer, ±9.7% for expert manual delineation, and ±10.0% for FIRST. Methods ranked the same for reproducibility of 1-year μL volume change, with LoA of ±218 μL for FreeSurfer, ±319 μL for expert manual delineation, and ±333 μL for FIRST. Approximate p-values indicated that reproducibility was better for FreeSurfer than for manual or FIRST, and that manual and FIRST did not differ. Inclusion of failed automated segmentations led to worsening of reproducibility of both automated methods for 1-year raw and percentage volume change. CONCLUSION Quantitative reproducibility values of 1-year microliter and percentage hippocampal volume change were roughly similar between expert manual outlining, FIRST and FreeSurfer, but FreeSurfer reproducibility was statistically significantly superior to both manual outlining and FIRST after exclusion of failed segmentations.
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Affiliation(s)
- Emma R Mulder
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
| | - Remko A de Jong
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
| | - Dirk L Knol
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - Ronald A van Schijndel
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Information and Communication Technology, VU University Medical Center, Amsterdam, The Netherlands
| | - Keith S Cover
- Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
| | - Pieter J Visser
- Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
| | - Hugo Vrenken
- Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands; Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands.
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11
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Frankó E, Joly O. Evaluating Alzheimer's disease progression using rate of regional hippocampal atrophy. PLoS One 2013; 8:e71354. [PMID: 23951142 PMCID: PMC3741167 DOI: 10.1371/journal.pone.0071354] [Citation(s) in RCA: 70] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2013] [Accepted: 06/28/2013] [Indexed: 11/19/2022] Open
Abstract
Alzheimer's disease (AD) is characterized by neurofibrillary tangle and neuropil thread deposition, which ultimately results in neuronal loss. A large number of magnetic resonance imaging studies have reported a smaller hippocampus in AD patients as compared to healthy elderlies. Even though this difference is often interpreted as atrophy, it is only an indirect measurement. A more direct way of measuring the atrophy is to use repeated MRIs within the same individual. Even though several groups have used this appropriate approach, the pattern of hippocampal atrophy still remains unclear and difficult to relate to underlying pathophysiology. Here, in this longitudinal study, we aimed to map hippocampal atrophy rates in patients with AD, mild cognitive impairment (MCI) and elderly controls. Data consisted of two MRI scans for each subject. The symmetric deformation field between the first and the second MRI was computed and mapped onto the three-dimensional hippocampal surface. The pattern of atrophy rate was similar in all three groups, but the rate was significantly higher in patients with AD than in control subjects. We also found higher atrophy rates in progressive MCI patients as compared to stable MCI, particularly in the antero-lateral portion of the right hippocampus. Importantly, the regions showing the highest atrophy rate correspond to those that were described to have the highest burden of tau deposition. Our results show that local hippocampal atrophy rate is a reliable biomarker of disease stage and progression and could also be considered as a method to objectively evaluate treatment effects.
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Affiliation(s)
- Edit Frankó
- INSERM U1075, Université de Caen Basse-Normandie, Caen, France.
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12
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Clerx L, van Rossum IA, Burns L, Knol DL, Scheltens P, Verhey F, Aalten P, Lapuerta P, van de Pol L, van Schijndel R, de Jong R, Barkhof F, Wolz R, Rueckert D, Bocchetta M, Tsolaki M, Nobili F, Wahlund LO, Minthon L, Frölich L, Hampel H, Soininen H, Visser PJ. Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment. Neurobiol Aging 2013; 34:2003-13. [PMID: 23540941 DOI: 10.1016/j.neurobiolaging.2013.02.002] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2013] [Accepted: 02/09/2013] [Indexed: 01/18/2023]
Abstract
Our aim was to compare the predictive accuracy of 4 different medial temporal lobe measurements for Alzheimer's disease (AD) in subjects with mild cognitive impairment (MCI). Manual hippocampal measurement, automated atlas-based hippocampal measurement, a visual rating scale (MTA-score), and lateral ventricle measurement were compared. Predictive accuracy for AD 2 years after baseline was assessed by receiver operating characteristics analyses with area under the curve as outcome. Annual cognitive decline was assessed by slope analyses up to 5 years after baseline. Correlations with biomarkers in cerebrospinal fluid (CSF) were investigated. Subjects with MCI were selected from the Development of Screening Guidelines and Clinical Criteria for Predementia AD (DESCRIPA) multicenter study (n = 156) and the single-center VU medical center (n = 172). At follow-up, area under the curve was highest for automated atlas-based hippocampal measurement (0.71) and manual hippocampal measurement (0.71), and lower for MTA-score (0.65) and lateral ventricle (0.60). Slope analysis yielded similar results. Hippocampal measurements correlated with CSF total tau and phosphorylated tau, not with beta-amyloid 1-42. MTA-score and lateral ventricle volume correlated with CSF beta-amyloid 1-42. We can conclude that volumetric hippocampal measurements are the best predictors of AD conversion in subjects with MCI.
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Affiliation(s)
- Lies Clerx
- Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht, the Netherlands.
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13
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Grothe M, Heinsen H, Teipel S. Longitudinal measures of cholinergic forebrain atrophy in the transition from healthy aging to Alzheimer's disease. Neurobiol Aging 2012; 34:1210-20. [PMID: 23158764 DOI: 10.1016/j.neurobiolaging.2012.10.018] [Citation(s) in RCA: 126] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2012] [Revised: 10/05/2012] [Accepted: 10/20/2012] [Indexed: 01/19/2023]
Abstract
Recent evidence from cross-sectional in vivo imaging studies suggests that atrophy of the cholinergic basal forebrain (BF) in Alzheimer's disease (AD) can be distinguished from normal age-related degeneration even at predementia stages of the disease. Longitudinal study designs are needed to specify the dynamics of BF degeneration in the transition from normal aging to AD. We applied recently developed techniques for in vivo volumetry of the BF to serial magnetic resonance imaging scans of 82 initially healthy elderly individuals (60-93 years) and 50 patients with very mild AD (Clinical Dementia Rating score = 0.5) that were clinically followed over an average of 3 ± 1.5 years. BF atrophy rates were found to be significantly higher than rates of global brain shrinkage even in cognitively stable healthy elderly individuals. Compared with healthy control subjects, very mild AD patients showed reduced BF volumes at baseline and increased volume loss over time. Atrophy of the BF was more pronounced in progressive patients compared with those that remained stable. The cholinergic BF undergoes disproportionate degeneration in the aging process, which is further increased by the presence of AD.
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Affiliation(s)
- Michel Grothe
- Department of Psychiatry, University of Rostock, Germany.
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14
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Knoops AJG, Gerritsen L, van der Graaf Y, Mali WPTM, Geerlings MI. Loss of entorhinal cortex and hippocampal volumes compared to whole brain volume in normal aging: the SMART-Medea study. Psychiatry Res 2012; 203:31-7. [PMID: 22910574 DOI: 10.1016/j.pscychresns.2011.12.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2011] [Revised: 11/30/2011] [Accepted: 12/06/2011] [Indexed: 11/26/2022]
Abstract
In non-demented elderly age-related decline in hippocampal volume has often been observed, but it is not clear if this loss is disproportionate relative to other brain tissue. Few studies examined age-related volume loss of the entorhinal cortex. We investigated the association of age with hippocampal and entorhinal cortex (ERC) volumes in a large sample of middle-aged and older persons without dementia. Within the SMART-Medea study, cross-sectional analyses were performed in 453 non-demented subjects (mean age 62±9 years, 81% male) with a history of arterial disease. Hippocampal and ERC volumes were assessed by manual segmentation on three-dimensional fast field-echo sequence T1-weighted magnetic resonance images. Automated segmentation was used to quantify volumes of BV and ICV. Hippocampal and ERC volumes were divided by intracranial volume (ICV) as well as total brain volume (BV) to determine whether age-related differences were disproportionate relative to other brain tissue. Total crude hippocampal volume was 5.96±0.7 ml and total crude ERC volume was 0.34±0.06 ml. Linear regression analyses adjusted for sex showed that with increasing age, hippocampal volume divided by ICV decreased (B per year older=-0.01 ml; 95% CI -0.02 to -0.004). However, no age-related decline in hippocampal volume relative to BV was observed (B per year older=0.005 ml; 95% CI -0.002 to 0.01). No age-related decline in ERC volume relative to ICV or BV was observed. In this population of nondemented patients with a history of vascular disease no age-related decline in entorhinal cortex volume was observed and although hippocampal volume decreased with age, it was not disproportionate relative to total brain volume.
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Affiliation(s)
- Arnoud J G Knoops
- University Medical Center Utrecht, Department of Radiology, Utrecht, The Netherlands
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15
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Wisse LEM, Gerritsen L, Zwanenburg JJM, Kuijf HJ, Luijten PR, Biessels GJ, Geerlings MI. Subfields of the hippocampal formation at 7T MRI: In vivo volumetric assessment. Neuroimage 2012; 61:1043-9. [PMID: 22440643 DOI: 10.1016/j.neuroimage.2012.03.023] [Citation(s) in RCA: 146] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2011] [Revised: 02/17/2012] [Accepted: 03/01/2012] [Indexed: 11/29/2022] Open
Affiliation(s)
- L E M Wisse
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
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16
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Hampel H, Wilcock G, Andrieu S, Aisen P, Blennow K, Broich K, Carrillo M, Fox NC, Frisoni GB, Isaac M, Lovestone S, Nordberg A, Prvulovic D, Sampaio C, Scheltens P, Weiner M, Winblad B, Coley N, Vellas B. Biomarkers for Alzheimer's disease therapeutic trials. Prog Neurobiol 2011; 95:579-93. [PMID: 21130138 DOI: 10.1016/j.pneurobio.2010.11.005] [Citation(s) in RCA: 96] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2010] [Revised: 11/10/2010] [Accepted: 11/22/2010] [Indexed: 11/26/2022]
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17
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Jack CR, Barkhof F, Bernstein MA, Cantillon M, Cole PE, Decarli C, Dubois B, Duchesne S, Fox NC, Frisoni GB, Hampel H, Hill DLG, Johnson K, Mangin JF, Scheltens P, Schwarz AJ, Sperling R, Suhy J, Thompson PM, Weiner M, Foster NL. Steps to standardization and validation of hippocampal volumetry as a biomarker in clinical trials and diagnostic criterion for Alzheimer's disease. Alzheimers Dement 2011; 7:474-485.e4. [PMID: 21784356 PMCID: PMC3396131 DOI: 10.1016/j.jalz.2011.04.007] [Citation(s) in RCA: 156] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2011] [Accepted: 04/26/2011] [Indexed: 11/15/2022]
Abstract
BACKGROUND The promise of Alzheimer's disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer's disease and thus represents the most rational target for an initial effort at standardization. METHODS AND RESULTS The authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer's Disease Centers-Alzheimer's Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer's Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark. CONCLUSIONS Although manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.
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18
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Frisoni GB, Fox NC, Jack CR, Scheltens P, Thompson PM. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol 2010; 6:67-77. [PMID: 20139996 PMCID: PMC2938772 DOI: 10.1038/nrneurol.2009.215] [Citation(s) in RCA: 1143] [Impact Index Per Article: 81.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Structural imaging based on magnetic resonance is an integral part of the clinical assessment of patients with suspected Alzheimer dementia. Prospective data on the natural history of change in structural markers from preclinical to overt stages of Alzheimer disease are radically changing how the disease is conceptualized, and will influence its future diagnosis and treatment. Atrophy of medial temporal structures is now considered to be a valid diagnostic marker at the mild cognitive impairment stage. Structural imaging is also included in diagnostic criteria for the most prevalent non-Alzheimer dementias, reflecting its value in differential diagnosis. In addition, rates of whole-brain and hippocampal atrophy are sensitive markers of neurodegeneration, and are increasingly used as outcome measures in trials of potentially disease-modifying therapies. Large multicenter studies are currently investigating the value of other imaging and nonimaging markers as adjuncts to clinical assessment in diagnosis and monitoring of progression. The utility of structural imaging and other markers will be increased by standardization of acquisition and analysis methods, and by development of robust algorithms for automated assessment.
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19
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Henneman WJP, Vrenken H, Barnes J, Sluimer IC, Verwey NA, Blankenstein MA, Klein M, Fox NC, Scheltens P, Barkhof F, van der Flier WM. Baseline CSF p-tau levels independently predict progression of hippocampal atrophy in Alzheimer disease. Neurology 2009; 73:935-40. [PMID: 19770469 DOI: 10.1212/wnl.0b013e3181b879ac] [Citation(s) in RCA: 58] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To investigate whether baseline CSF biomarkers are associated with hippocampal atrophy rate as a measure of disease progression in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls, controlling for baseline neuropsychological and MRI findings. METHODS We assessed data from 31 patients with AD, 25 patients with MCI, and 19 controls (mean age 68 +/- 8 years; 39 [52%] female) who visited our memory clinic and had received serial MRI scanning (scan interval 1.7 +/- 0.7 years). At baseline, CSF biomarkers (amyloid beta 1-42, tau, and tau phosphorylated at threonine 181 [p-tau]) were obtained, as well as neuropsychological data. Baseline MRI scans were assessed using visual rating scales for medial temporal lobe atrophy (MTA), global cortical atrophy, and white matter hyperintensities. Hippocampal atrophy rates were estimated using regional nonlinear "fluid" registration of follow-up scan to baseline scan. RESULTS Stepwise multiple linear regression, adjusted for age and sex, showed that increased CSF p-tau levels (beta [standard error]: -0.79 [0.35]) at baseline was independently associated with higher subsequent hippocampal atrophy rates (p < 0.05), together with poorer memory performance (0.09 [0.04]) and more severe MTA (-0.60 [0.21]). The association of memory function with hippocampal atrophy rate was explained by the link with diagnosis, because it disappeared from the model after we additionally corrected for diagnosis. CONCLUSIONS Baseline CSF levels of tau phosphorylated at threonine 181 are independently associated with subsequent disease progression, as reflected by hippocampal atrophy rate. This effect is independent of baseline neuropsychological and MRI predictors. Our results imply that predicting disease progression can best be achieved by combining information from different modalities.
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Affiliation(s)
- W J P Henneman
- Department of Radiology and Alzheimer Center, VU University Medical Center, 1007 MB Amsterdam, The Netherlands.
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20
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Morra JH, Tu Z, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N, Hua X, Toga AW, Jack CR, Schuff N, Weiner MW, Thompson PM. Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls. Hum Brain Mapp 2009; 30:2766-88. [PMID: 19172649 PMCID: PMC2733926 DOI: 10.1002/hbm.20708] [Citation(s) in RCA: 150] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2008] [Revised: 09/03/2008] [Accepted: 11/02/2008] [Indexed: 11/05/2022] Open
Abstract
We used a new method we developed for automated hippocampal segmentation, called the auto context model, to analyze brain MRI scans of 400 subjects from the Alzheimer's disease neuroimaging initiative. After training the classifier on 21 hand-labeled expert segmentations, we created binary maps of the hippocampus for three age- and sex-matched groups: 100 subjects with Alzheimer's disease (AD), 200 with mild cognitive impairment (MCI) and 100 elderly controls (mean age: 75.84; SD: 6.64). Hippocampal traces were converted to parametric surface meshes and a radial atrophy mapping technique was used to compute average surface models and local statistics of atrophy. Surface-based statistical maps visualized links between regional atrophy and diagnosis (MCI versus controls: P = 0.008; MCI versus AD: P = 0.001), mini-mental state exam (MMSE) scores, and global and sum-of-boxes clinical dementia rating scores (CDR; all P < 0.0001, corrected). Right but not left hippocampal atrophy was associated with geriatric depression scores (P = 0.004, corrected); hippocampal atrophy was not associated with subsequent decline in MMSE and CDR scores, educational level, ApoE genotype, systolic or diastolic blood pressure measures, or homocysteine. We gradually reduced sample sizes and used false discovery rate curves to examine the method's power to detect associations with diagnosis and cognition in smaller samples. Forty subjects were sufficient to discriminate AD from normal and correlate atrophy with CDR scores; 104, 200, and 304 subjects, respectively, were required to correlate MMSE with atrophy, to distinguish MCI from normal, and MCI from AD.
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Affiliation(s)
- Jonathan H. Morra
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Zhuowen Tu
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Liana G. Apostolova
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
- Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Amity E. Green
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
- Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Christina Avedissian
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Sarah K. Madsen
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Neelroop Parikshak
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Xue Hua
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | - Arthur W. Toga
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
| | | | - Norbert Schuff
- Department of Veterans Affairs Medical Center, and Department of Radiology, UC San Francisco, San Francisco, California
| | - Michael W. Weiner
- Department of Veterans Affairs Medical Center, and Department of Radiology, UC San Francisco, San Francisco, California
- Department of Medicine and Psychiatry, UC San Francisco, San Francisco, California
| | - Paul M. Thompson
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
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In vivo hippocampal measurement and memory: a comparison of manual tracing and automated segmentation in a large community-based sample. PLoS One 2009; 4:e5265. [PMID: 19370155 PMCID: PMC2667216 DOI: 10.1371/journal.pone.0005265] [Citation(s) in RCA: 89] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2008] [Accepted: 03/13/2009] [Indexed: 12/29/2022] Open
Abstract
While manual tracing is the method of choice in measuring hippocampal volume, its time intensive nature and proneness to human error make automated methods attractive, especially when applied to large samples. Few studies have systematically compared the performance of the two techniques. In this study, we measured hippocampal volumes in a large (N = 403) population-based sample of individuals aged 44–48 years using manual tracing by a trained researcher and automated procedure using Freesurfer (http://surfer.nmr.mgh.harvard.edu) imaging suite. Results showed that absolute hippocampal volumes assessed with these methods were significantly different, with automated measures using the Freesurfer software suite being significantly larger, by 23% for the left and 29% for the right hippocampus. The correlation between the two methods varied from 0.61 to 0.80, with lower correlations for hippocampi with visible abnormalities. Inspection of 2D and 3D models suggested that this difference was largely due to greater inclusion of boundary voxels by the automated method and variations in subiculum/entorhinal segmentation. The correlation between left and right hippocampal volumes was very similar by the two methods. The relationship of hippocampal volumes to selected sociodemographic and cognitive variables was not affected by the measurement method, with each measure showing an association with memory performance and suggesting that both were equally valid for this purpose. This study supports the use of automated measures, based on Freesurfer in this instance, as being sufficiently reliable and valid particularly in the context of larger sample sizes when the research question does not rely on ‘true’ hippocampal volumes.
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Leow AD, Yanovsky I, Parikshak N, Hua X, Lee S, Toga AW, Jack CR, Bernstein MA, Britson PJ, Gunter JL, Ward CP, Borowski B, Shaw LM, Trojanowski JQ, Fleisher AS, Harvey D, Kornak J, Schuff N, Alexander GE, Weiner MW, Thompson PM. Alzheimer's disease neuroimaging initiative: a one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition. Neuroimage 2009; 45:645-55. [PMID: 19280686 PMCID: PMC2696624 DOI: 10.1016/j.neuroimage.2009.01.004] [Citation(s) in RCA: 138] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Tensor-based morphometry can recover three-dimensional longitudinal brain changes over time by nonlinearly registering baseline to follow-up MRI scans of the same subject. Here, we compared the anatomical distribution of longitudinal brain structural changes, over 12 months, using a subset of the ADNI dataset consisting of 20 patients with Alzheimer's disease (AD), 40 healthy elderly controls, and 40 individuals with mild cognitive impairment (MCI). Each individual longitudinal change map (Jacobian map) was created using an unbiased registration technique, and spatially normalized to a geometrically-centered average image based on healthy controls. Voxelwise statistical analyses revealed regional differences in atrophy rates, and these differences were correlated with clinical measures and biomarkers. Consistent with prior studies, we detected widespread cerebral atrophy in AD, and a more restricted atrophic pattern in MCI. In MCI, temporal lobe atrophy rates were correlated with changes in mini-mental state exam (MMSE) scores, clinical dementia rating (CDR), and logical/verbal learning memory scores. In AD, temporal atrophy rates were correlated with several biomarker indices, including a higher CSF level of p-tau protein, and a greater CSF tau/beta amyloid 1-42 (ABeta42) ratio. Temporal lobe atrophy was significantly faster in MCI subjects who converted to AD than in non-converters. Serial MRI scans can therefore be analyzed with nonlinear image registration to relate ongoing neurodegeneration to a variety of pathological biomarkers, cognitive changes, and conversion from MCI to AD, tracking disease progression in 3-dimensional detail.
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Affiliation(s)
- Alex D Leow
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095-1769, USA.
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23
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Henneman WJP, Sluimer JD, Barnes J, van der Flier WM, Sluimer IC, Fox NC, Scheltens P, Vrenken H, Barkhof F. Hippocampal atrophy rates in Alzheimer disease: added value over whole brain volume measures. Neurology 2009; 72:999-1007. [PMID: 19289740 PMCID: PMC2821835 DOI: 10.1212/01.wnl.0000344568.09360.31] [Citation(s) in RCA: 243] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To investigate the added value of hippocampal atrophy rates over whole brain volume measurements on MRI in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls. METHODS We included 64 patients with AD (67 +/- 9 years; F/M 38/26), 44 patients with MCI (71 +/- 6 years; 21/23), and 34 controls (67 +/- 9 years; 16/18). Two MR scans were performed (scan interval: 1.8 +/- 0.7 years; 1.0 T), using a coronal three-dimensional T1-weighted gradient echo sequence. At follow-up, 3 controls and 23 patients with MCI had progressed to AD. Hippocampi were manually delineated at baseline. Hippocampal atrophy rates were calculated using regional, nonlinear fluid registration. Whole brain baseline volumes and atrophy rates were determined using automated segmentation and registration tools. RESULTS All MRI measures differed between groups (p < 0.005). For the distinction of MCI from controls, larger effect sizes of hippocampal measures were found compared to whole brain measures. Between MCI and AD, only whole brain atrophy rate differed significantly. Cox proportional hazards models (variables dichotomized by median) showed that within all patients without dementia, hippocampal baseline volume (hazard ratio [HR]: 5.7 [95% confidence interval: 1.5-22.2]), hippocampal atrophy rate (5.2 [1.9-14.3]), and whole brain atrophy rate (2.8 [1.1-7.2]) independently predicted progression to AD; the combination of low hippocampal volume and high atrophy rate yielded a HR of 61.1 (6.1-606.8). Within patients with MCI, only hippocampal baseline volume and atrophy rate predicted progression. CONCLUSION Hippocampal measures, especially hippocampal atrophy rate, best discriminate mild cognitive impairment (MCI) from controls. Whole brain atrophy rate discriminates Alzheimer disease (AD) from MCI. Regional measures of hippocampal atrophy are the strongest predictors of progression to AD.
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Affiliation(s)
- W J P Henneman
- Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands.
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24
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Morra JH, Tu Z, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N, Hua X, Toga AW, Jack CR, Weiner MW, Thompson PM. Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controls. Neuroimage 2008; 43:59-68. [PMID: 18675918 PMCID: PMC2624575 DOI: 10.1016/j.neuroimage.2008.07.003] [Citation(s) in RCA: 161] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2007] [Revised: 05/27/2008] [Accepted: 07/02/2008] [Indexed: 11/30/2022] Open
Abstract
We introduce a new method for brain MRI segmentation, called the auto context model (ACM), to segment the hippocampus automatically in 3D T1-weighted structural brain MRI scans of subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). In a training phase, our algorithm used 21 hand-labeled segmentations to learn a classification rule for hippocampal versus non-hippocampal regions using a modified AdaBoost method, based on approximately 18,000 features (image intensity, position, image curvatures, image gradients, tissue classification maps of gray/white matter and CSF, and mean, standard deviation, and Haar filters of size 1x1x1 to 7x7x7). We linearly registered all brains to a standard template to devise a basic shape prior to capture the global shape of the hippocampus, defined as the pointwise summation of all the training masks. We also included curvature, gradient, mean, standard deviation, and Haar filters of the shape prior and the tissue classified images as features. During each iteration of ACM - our extension of AdaBoost - the Bayesian posterior distribution of the labeling was fed back in as an input, along with its neighborhood features as new features for AdaBoost to use. In validation studies, we compared our results with hand-labeled segmentations by two experts. Using a leave-one-out approach and standard overlap and distance error metrics, our automated segmentations agreed well with human raters; any differences were comparable to differences between trained human raters. Our error metrics compare favorably with those previously reported for other automated hippocampal segmentations, suggesting the utility of the approach for large-scale studies.
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Affiliation(s)
- Jonathan H Morra
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095-1769, USA
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25
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Eckerström C, Olsson E, Borga M, Ekholm S, Ribbelin S, Rolstad S, Starck G, Edman A, Wallin A, Malmgren H. Small baseline volume of left hippocampus is associated with subsequent conversion of MCI into dementia: the Göteborg MCI study. J Neurol Sci 2008; 272:48-59. [PMID: 18571674 DOI: 10.1016/j.jns.2008.04.024] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2007] [Revised: 03/17/2008] [Accepted: 04/17/2008] [Indexed: 11/19/2022]
Abstract
BACKGROUND Earlier studies have reported that hippocampal atrophy can to some extent predict which patients with mild cognitive impairment (MCI) will subsequently convert to dementia, and that converters have an enhanced rate of hippocampal volume loss. OBJECTIVE To further validate the hypothesis that hippocampal atrophy predicts conversion from MCI to dementia, to relate baseline hippocampal volume to different forms of dementia, and to investigate the role of hippocampal side differences and rate of volume loss over time. PATIENTS The subjects (N=68) include patients with MCI at baseline and progression to dementia at the two-year follow-up (N=21), stable MCI patients (N=21), and controls (N=26). Among the progressing patients, 13 were diagnosed as having AD. METHODS The Göteborg MCI study is a clinically based longitudinal study with biannual clinical assessments. Hippocampal volumetry was performed manually on the MRI investigations at baseline and at the two-year follow-up. RESULTS Hippocampal volumetry could predict conversion to dementia in both the AD and the non-AD subgroup of converters. Left hippocampal volume in particular discriminated between converting and stable MCI. Cut off points for individual discrimination were shown to be potentially useful. The converting MCI group had a significantly higher rate of hippocampal volume loss as compared to the stable MCI group. CONCLUSIONS In MCI patients, hippocampal volumetry at baseline gives prognostic information about possible development of AD and non-AD dementia. Contrary to earlier studies, we found that left hippocampal volume has the best predictive power. Reliable predictions appear to be possible in many individual cases.
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Affiliation(s)
- C Eckerström
- Institute of Neuroscience and Physiology, Göteborg University, Sweden
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26
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Abstract
Dementia represents one of the major public health problems facing ageing populations, with 20% of those over 80 years of age suffering from this disorder. The advent of therapeutic agents has brought about an increasing demand for a more accurate and earlier diagnosis, and the value of neuroimaging in improving the diagnostic process is becoming widely accepted. Neuroimaging assessments may add weight to a diagnosis of neurodegeneration as opposed to healthy ageing, improve the differential diagnosis, aid in the prediction of conversion to dementia in individuals at a higher risk of developing the disorder, track disease progression and provide an outcome measure for assessment of drug efficacy.
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Affiliation(s)
- R I Scahill
- Dementia Research Centre, 8-11 Queen Square, London WC1N 3BG, UK.
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27
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Camara O, Schnabel JA, Ridgway GR, Crum WR, Douiri A, Scahill RI, Hill DLG, Fox NC. Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images. Neuroimage 2008; 42:696-709. [PMID: 18571436 DOI: 10.1016/j.neuroimage.2008.04.259] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2007] [Revised: 04/21/2008] [Accepted: 04/24/2008] [Indexed: 11/29/2022] Open
Abstract
The evaluation of atrophy quantification methods based on magnetic resonance imaging have been usually hindered by the lack of realistic gold standard data against which to judge these methods or to help refine them. Recently [Camara, O., Schweiger, M., Scahill, R., Crum, W., Sneller, B., Schnabel, J., Ridgway, G., Cash, D., Hill, D., Fox, N., 2006. Phenomenological model of diffuse global and regional atrophy using finite-element methods. IEEE Trans. Med.l Imaging 25, 1417-1430], we presented a technique in which atrophy is realistically simulated in different tissue compartments or neuroanatomical structures with a phenomenological model. In this study, we have generated a cohort of realistic simulated Alzheimer's disease (AD) images with known amounts of atrophy, mimicking a set of 19 real controls and 27 probable AD subjects, with an improved version of our atrophy simulation methodology. This database was then used to assess the accuracy of several well-known computational anatomy methods which provide global (BSI and SIENA) or local (Jacobian integration) estimates of longitudinal atrophy in brain structures using MR images. SIENA and BSI results correlated very well with gold standard data (Pearson coefficient of 0.962 and 0.969 respectively), achieving small mean absolute differences with respect to the gold standard (percentage change from baseline volume): BSI of 0.23%+/-0.26%; SIENA of 0.22%+/-0.28%. Jacobian integration was guided by both fluid and FFD-based registration techniques and resulting deformation fields and associated Jacobians were compared, region by region, with gold standard ones. The FFD-based technique outperformed the fluid one in all evaluated structures (mean absolute differences from the gold standard in percentage change from baseline volume): whole brain, FFD=0.31%, fluid=0.58%; lateral ventricles, FFD=0.79%; fluid=1.45%; left hippocampus, FFD=0.82%; fluid=1.42%; right hippocampus, FFD=0.95%; fluid=1.62%. The largest errors for both local techniques occurred in the sulcal CSF (FFD=2.27%; fluid=3.55%) regions. For large structures such as the whole brain, these mean absolute differences, relative to the applied atrophy, represented similar percentages for the BSI, SIENA and FFD techniques (controls/patients): BSI, 51.99%/16.36%; SIENA, 62.34%/21.59%; FFD, 41.02%/24.95%. For small structures such as the hippocampi, these percentages were larger, especially for controls where errors were approximately equal to the small applied changes (controls/patients): FFD, 92.82%/43.61%. However, these apparently large relative errors have not prevented the global or hippocampal measures from finding significant group separation in our study. The evaluation framework presented here will help in quantifying whether the accuracy of future methodological developments is sufficient for analysing change in smaller or less atrophied local brain regions. Results obtained in our experiments with realistic simulated data confirm previously published estimates of accuracy for both evaluated global techniques. Regarding Jacobian Integration methods, the FFD-based one demonstrated promising results and potential for being used in clinical studies alongside (or in place of) the more common global methods. The generated gold standard data has also allowed us to identify some stages and sets of parameters in the evaluated techniques--the brain extraction step in the global techniques and the number of multi-resolution levels and the stopping criteria in the registration-based methods--that are critical for their accuracy.
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Affiliation(s)
- Oscar Camara
- Centre for Medical Image Computing, Department of Medical Physics and Bioengineering, University College London, WC1E 6BT, UK
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28
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Spatiotemporal normalization for longitudinal analysis of gray matter atrophy in frontotemporal dementia. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2008; 10:303-10. [PMID: 18044582 DOI: 10.1007/978-3-540-75759-7_37] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
We present a unified method, based on symmetric diffeomorphisms, for studying longitudinal neurodegeneration. Our method first uses symmetric diffeomorphic normalization to find a spatiotemporal parameterization of an individual's image time series. The second step involves mapping a representative image or set of images from the time series into an optimal template space. The template mapping is then combined with the intrasubject spatiotemporal map to enable pairwise statistical tests to be performed on a population of normalized time series images. Here, we apply this longitudinal analysis protocol to study the gray matter atrophy patterns induced by frontotemporal dementia (FTD). We sample our normalized spatiotemporal maps at baseline (time zero) and time one year to generate an annualized atrophy map (AAM) that estimates the annual effect of FTD. This spatiotemporal normalization enables us to locate neuroanatomical regions that consistently undergo significant annual gray matter atrophy across the population. We found the majority of annual atrophy to occur in the frontal and temporal lobes in our population of 20 subjects. We also found significant effects in the hippocampus, insula and cingulate gyrus. Our novel results, significant at p < 0.05 after false discovery rate correction, are represented in local template space but also assigned Talairach coordinates and Brodmann and Anatomical Automatic Labeling (AAL) labels. This paper shows the statistical power of symmetric diffeomorphic normalization for performing deformation-based studies of longitudinal atrophy.
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